A survey of Web clustering engines

Author:

Carpineto Claudio1,Osiński Stanislaw2,Romano Giovanni1,Weiss Dawid3

Affiliation:

1. Fondazione Ugo Bordoni, Roma, Italy

2. Carrot Search

3. Poznan University of Technology, Poznan, Poland

Abstract

Web clustering engines organize search results by topic, thus offering a complementary view to the flat-ranked list returned by conventional search engines. In this survey, we discuss the issues that must be addressed in the development of a Web clustering engine, including acquisition and preprocessing of search results, their clustering and visualization. Search results clustering, the core of the system, has specific requirements that cannot be addressed by classical clustering algorithms. We emphasize the role played by the quality of the cluster labels as opposed to optimizing only the clustering structure. We highlight the main characteristics of a number of existing Web clustering engines and also discuss how to evaluate their retrieval performance. Some directions for future research are finally presented.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Cited by 209 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Web Search Engine Results Page Viewing Formats for Different Search Tasks;International Journal of Human–Computer Interaction;2024-07-29

2. A Case and Cluster-Based Framework for Reuse and Prioritization in Software Testing;Proceedings of the 20th Brazilian Symposium on Information Systems;2024-05-20

3. GRAFS: Graphical Faceted Search System to Support Conceptual Understanding in Exploratory Search;ACM Transactions on Interactive Intelligent Systems;2023-05-05

4. The vision of on-demand architectural knowledge systems as a decision-making companion;Journal of Systems and Software;2023-04

5. Improve Firefly Heuristic Optimization Scheme for Web based Information Retrieval;2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS);2023-02-24

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3